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Land Cover Based Landscape Pattern Dynamics of Anhui Province Using GlobCover and MCD12Q1 Global Land Cover Products

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  • Jinling Zhao

    (National Joint Engineering Research Center for Analysis and Application of Agro-Ecological Big Data, Anhui University, Hefei 230601, China)

  • Jie Wang

    (Key Laboratory of Intelligent Computing & Signal Processing, Ministry of Education, Anhui University, Hefei 230039, China)

  • Yu Jin

    (Key Laboratory of Intelligent Computing & Signal Processing, Ministry of Education, Anhui University, Hefei 230039, China)

  • Lingling Fan

    (Key Laboratory of Intelligent Computing & Signal Processing, Ministry of Education, Anhui University, Hefei 230039, China)

  • Chao Xu

    (National Joint Engineering Research Center for Analysis and Application of Agro-Ecological Big Data, Anhui University, Hefei 230601, China)

  • Dong Liang

    (National Joint Engineering Research Center for Analysis and Application of Agro-Ecological Big Data, Anhui University, Hefei 230601, China)

  • Linsheng Huang

    (National Joint Engineering Research Center for Analysis and Application of Agro-Ecological Big Data, Anhui University, Hefei 230601, China)

Abstract

The development and free distribution of global land cover (GLC) products have greatly assisted in the evolution and analysis of relationships between land cover and landscape pattern. In this study, GlobCover and MCD12Q1 GLC datasets of 2005 and 2009 were comparatively used to analyze the variation of land cover in Anhui Province, China at both the class and landscape scale. The land cover classification schemes of both datasets were firstly reclassified to six types of forestland, grassland, wetland, cropland, artificial area, and others, and then FRAGSTATS was used to calculate the landscape indices. The results showed that from 2005 to 2009, the area density of ‘cropland’ landscape decreased, and it increased for ‘wetland’ and ‘artificial area’. The landscape fragmentation of ‘forestland’ and ‘grassland’ were larger. Moreover, over the same period, the class edge (CE) of ‘cropland’ was diminished; while the CE of ‘wetland’ was enhanced and the aggregation became larger. Conversely, the aggregation and shape complexity of ‘artificial area’ remained the same. The clumpiness index (CLUMPY) of ‘cropland’ varied from 0.8995 to 0.9050, indicating a higher aggregation and more concentrated distribution. The heterogeneity index (HT) value of MCD12Q1 and GlobCover datasets varied, respectively, from 0.9642 to 0.9053 and from 0.8867 to 0.8751, demonstrating that the landscape heterogeneity of Anhui Province was reduced from 2005 to 2009. Driving force analysis (DFA) was just performed for ‘artificial area’, ‘cropland’, and ‘wetland’ according to the 2005–2009 statistical yearbook data, because they were apt to be affected by human activities over a relatively short period of time.

Suggested Citation

  • Jinling Zhao & Jie Wang & Yu Jin & Lingling Fan & Chao Xu & Dong Liang & Linsheng Huang, 2018. "Land Cover Based Landscape Pattern Dynamics of Anhui Province Using GlobCover and MCD12Q1 Global Land Cover Products," Sustainability, MDPI, vol. 10(4), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1285-:d:142500
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    References listed on IDEAS

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    1. Martin Herold & Joseph Scepan & Keith C Clarke, 2002. "The Use of Remote Sensing and Landscape Metrics to Describe Structures and Changes in Urban Land Uses," Environment and Planning A, , vol. 34(8), pages 1443-1458, August.
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    Keywords

    landscape pattern; global land cover; GlobCover; MCD12Q1;
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